{"title":"An efficient method for the detection of multiple concentric circles","authors":"X. Cao, F. Deravi","doi":"10.1109/ICASSP.1992.226257","DOIUrl":null,"url":null,"abstract":"The authors extend the alternative Hough transform method for the detection of multiple circles proposed by the authors (1990) to the detection of multiple concentric circles contained in an image. The parameters of a circle are determined by the groups of three edge points on the circle. The extension of the proposed rules to search for the three edge points ensures that every member of a group will be on the same circle, either on the inner circle or on the outer one, instead of some of them lying on the inner circle and some of them lying on the outer one. The application of the proposed method to a noisy gray-scale image containing washers shows that the clusters representing circle centers in the parameter space are much more compact than those obtained by the original Hough method for circle detection without involving postprocessing operations.<<ETX>>","PeriodicalId":163713,"journal":{"name":"[Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"[Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.1992.226257","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
The authors extend the alternative Hough transform method for the detection of multiple circles proposed by the authors (1990) to the detection of multiple concentric circles contained in an image. The parameters of a circle are determined by the groups of three edge points on the circle. The extension of the proposed rules to search for the three edge points ensures that every member of a group will be on the same circle, either on the inner circle or on the outer one, instead of some of them lying on the inner circle and some of them lying on the outer one. The application of the proposed method to a noisy gray-scale image containing washers shows that the clusters representing circle centers in the parameter space are much more compact than those obtained by the original Hough method for circle detection without involving postprocessing operations.<>